Optimizing CPU Cache Utilization in Cloud VMs with Accurate Cache Abstraction
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915647751979008 |
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| author | Tofigh, Mani Guo, Edward Jia, Weiwei Ding, Xiaoning Zhao, Zirui Neil Shan, Jianchen |
| author_facet | Tofigh, Mani Guo, Edward Jia, Weiwei Ding, Xiaoning Zhao, Zirui Neil Shan, Jianchen |
| contents | This paper shows that cache-based optimizations are often ineffective in cloud virtual machines (VMs) due to limited visibility into and control over provisioned caches. In public clouds, CPU caches can be partitioned or shared among VMs, but a VM is unaware of cache provisioning details. Moreover, a VM cannot influence cache usage via page placement policies, as memory-to-cache mappings are hidden. The paper proposes a novel solution, CacheX, which probes accurate and fine-grained cache abstraction within VMs using eviction sets without requiring hardware or hypervisor support, and showcases the utility of the probed information with two new techniques: LLC contention-aware task scheduling and virtual color-aware page cache management. Our evaluation of CacheX's implementation in x86 Linux kernel demonstrates that it can effectively improve cache utilization for various workloads in public cloud VMs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_09956 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Optimizing CPU Cache Utilization in Cloud VMs with Accurate Cache Abstraction Tofigh, Mani Guo, Edward Jia, Weiwei Ding, Xiaoning Zhao, Zirui Neil Shan, Jianchen Distributed, Parallel, and Cluster Computing Operating Systems Performance This paper shows that cache-based optimizations are often ineffective in cloud virtual machines (VMs) due to limited visibility into and control over provisioned caches. In public clouds, CPU caches can be partitioned or shared among VMs, but a VM is unaware of cache provisioning details. Moreover, a VM cannot influence cache usage via page placement policies, as memory-to-cache mappings are hidden. The paper proposes a novel solution, CacheX, which probes accurate and fine-grained cache abstraction within VMs using eviction sets without requiring hardware or hypervisor support, and showcases the utility of the probed information with two new techniques: LLC contention-aware task scheduling and virtual color-aware page cache management. Our evaluation of CacheX's implementation in x86 Linux kernel demonstrates that it can effectively improve cache utilization for various workloads in public cloud VMs. |
| title | Optimizing CPU Cache Utilization in Cloud VMs with Accurate Cache Abstraction |
| topic | Distributed, Parallel, and Cluster Computing Operating Systems Performance |
| url | https://arxiv.org/abs/2511.09956 |